Impact of changes in pruning practices on vine growth and yield

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

In China’s social media-driven marketing landscape, user-generated content (UGC) plays a pivotal role in brand communication and consumer decision-making.

Climate change and reduction of inputs are two major challenges for viticulture and oenology. With increasing temperature, wines become less acid and microbiologically less stable (1).

Winemaking generates significant amounts of by-products, such as grape pomace and wine lees, which are primarily used for distillation and composting.

Malolactic fermentation (MLF) is a secondary wine fermentation conducted by lactic acid bacteria (LAB). This fermentation is important in winemaking as it deacidifies the wine, converting L-malic acid into L-lactic acid and carbon dioxide, and it contributes to microbial stability. Wine pH is highly selective, and at pH below 3.5 generally only strains of O. oeni can survive and express malolactic activity, while under more favorable growth conditions above pH 3.5, species of Lactobacillus and Pediococcus may conduct the MLF. Among the LAB species Lactiplantibacillus plantarum strains have shown most interesting results under hot climate conditions, not only for their capacity to induce MLF, but also for their homo-fermentative properties towards hexose sugars, which makes them suitable for induction of MLF in high pH and high alcohol wines, when inoculated at the beginning of alcoholic fermentation.